Optimal irrigation planning in river basin development: The case of the Upper Cauvery river basin

The study deals with the irrigation planning of the Cauvery river basin in peninsular India which is extensively developed in the downstream reaches and has a high potential for development in the upper reaches. A four-reservoir system is modelled on a monthly basis by using a mathematical programming (LP) formulation to find optimum cropping patterns, subject to land, water and downstream release constraints, and applied to the Cauvery basin. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analysed in the context of multiobjective planning and the trade-offs discussed.

Puccinia psidii in Queensland, Australia: disease symptoms, distribution and impact

Puccinia psidii has long been considered a significant threat to Australian plant industries and ecosystems. In April 2010, P. psidii was detected for the first time in Australia on the central coast of New South Wales (NSW). The fungus spread rapidly along the east coast and in December 2010 was found in Queensland (Qld) followed by Victoria a year later. Puccinia psidii was initially restricted to the southeastern part of Qld but spread as far north as Mossman. In Qld, 48 species of Myrtaceae are considered highly or extremely susceptible to the disease. The impact of P. psidii on individual trees and shrubs has ranged from minor leaf spots, foliage, stem and branch dieback to reduced fecundity. Tree death, as a result of repeated infection, has been recorded for Rhodomyrtus psidioides. Rust infection has also been recorded on flower buds, flowers and fruits of 28 host species. Morphological and molecular characteristics were used to confirm the identification of P. psidii from a range of Myrtaceae in Qld and compared with isolates from NSW and overseas. A reconstructed phylogeny based on the LSU and SSU regions of rDNA did not resolve the familial placement of P. psidii, but indicated that it does not belong to the Pucciniaceae. Uredo rangelii was found to be con-specific with all isolates of P. psidii in morphology, ITS and LSU sequence data, and host range.

Freeze-drying of ovalbumin loaded mesoporous silica nanoparticle vaccine formulation increases antigen stability under ambient conditions

Amino functionalised mesoporous silica nanoparticles (AM-41) have been identified as a promising vaccine delivery material. The capacity of AM-41 to stabilise vaccine components at ambient temperature (23–27 °C) was determined by adsorbing the model antigen ovalbumin (OVA) to AM-41 particles (OVA-41). The OVA-41 was successfully freeze-dried using the excipients 5% trehalose and 1% PEG8000. Both the immunological activity of OVA and the nanoparticle structure were maintained following two months storage at ambient temperature. The results of immunisation studies in mice with reconstituted OVA-41 demonstrated the induction of humoral and cell-meditated immune responses. The capacity of AM-41 particles to facilitate ambient storage of vaccine components without loss of immunological potency will underpin the further development of this promising vaccine delivery platform.

Data distribution and task scheduling for distributed computing of all-to-all comparison problems

This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

Active vibration suppression of non-linear beams using optimal dynamic inversion

Euler–Bernoulli beams are distributed parameter systems that are governed by a non-linear partial differential equation (PDE) of motion. This paper presents a vibration control approach for such beams that directly utilizes the non-linear PDE of motion, and hence, it is free from approximation errors (such as model reduction, linearization etc.). Two state feedback controllers are presented based on a newly developed optimal dynamic inversion technique which leads to closed-form solutions for the control variable. In one formulation a continuous controller structure is assumed in the spatial domain, whereas in the other approach it is assumed that the control force is applied through a finite number of discrete actuators located at predefined discrete locations in the spatial domain. An implicit finite difference technique with unconditional stability has been used to solve the PDE with control actions. Numerical simulation studies show that the beam vibration can effectively be decreased using either of the two formulations.

Charge distribution, dipole moments and molecular structure of some organogermanium compounds

Formal charge distributions in, and the electric dipole moments of, a few simple organogermanium compounds have been evaluated by the method of R. P. Smith et al. [J. Amer. Chem. Soc., 73(1951) 2263]. The difference between the experimental and calculated moments in the case of alkylhalogermanes is explained in terms of the pπ—dπ back bonding effect outweighing the electron releasing effect. In unsaturated compounds, the differences are attributed to possible mesmeric effects involving the expansion of the germanium valence shell.

Tailoring polyolefin properties by metallocene catalysis

This doctoral thesis deals with the syntheses of olefin homo- and copolymers using different kind of metallocene catalyst. Ethene, propene, 1-hexene, 1-hexadecene, vinylcyclohexane and phenylnorbornene were homo- or copolymerized with the catalysts. The unbridged benzyl substituted zirconium dichloride catalysts (1-4), ansa- bridged acenaphtyl substituted zirconium dichloride catalysts, ( 5, 6), rac- and meso-ethylene-bis(1-indenyl)zirconium dichlorides, (rac- and meso-8), rac-ethylene-bis(1-indenyl)hafnium dichloride, ( 12), bis(9-fluorenyl)hafnium dichloride (14 ) enantiomerically pure (R)- phenylethyl[(9-fluorenyl-1-indenyl)]ZrCl2, (11), 14 and asymmetric dimethylsilyl[(3-benzylindenyl-(2-methylbenzen[e]indenyl)] zirconium dichloride, (13), were prepared in our laboratory. Dimethylsilyl-bis(1-indenyl)zirconium dichloride, (9), isopropylidene(9-fluorenyl-cyclopentadienyl)zirconium dichloride, (10), and were obtained commercially. The solid-state structures of the catalysts rac- and meso-1 were determined by X-ray crystallography. Computational methods were used for the structure optimization of the catalyst rac- and meso-1 in order to compare the theoretical calculations with the experimental results. Polymerization experiments were conducted in a highly purified autoclave system using low pressures (< 5 bar) of gaseous monomers. The experiments were designed to attain the optimal catalytic activity and a uniform copolymer composition. The prepared homo- and copolymers were characterized by the gel permeation chromatography, GPC, differential scanning calorimetry, DSC, nuclear magnetic resonance, NMR, and Fourier transform infrared spectrometry, FTIR . Molar mass (Mw, Mn), molar mass distribution (Mw/Mn), tacticity, comonomer content, melting temperature, glass transition temperature, and end group structures and content were determined. A special attention was paid on the correlation of the polymer properties with the catalyst structures and polymerization conditions. An intramolecular phenyl coordination was found in phenyl substituted benzyl zirconocenes 1-3 explaining the decreased activity of the catalysts. Novel copolymers poly(propene-co-phenylnorbornene) and poly(propene co-vinylcyclohexane), were synthesized and high molar mass poly(ethene-co-1-hexene) and poly(ethene-co-1-hexadecene) copolymers with elastic properties were prepared. Activation of a hafnocene catalyst was studied with UV-Vis spectrometry and activation process for the synthesis of ultra high molar mass poly(1-hexene) was found out.

Influence of dingoes on sheep distribution in Australia

Objective To describe the influence of the dingo (Canis lupus dingo) on the past, present and future distributions of sheep in Australia. Design The role of the dingo in the rise and fall of sheep numbers is reviewed, revised data are provided on the present distribution and density of sheep and dingoes, and historical patterns of sheep distribution are used to explore the future of rangeland sheep grazing. Results Dingoes are a critical causal factor in the distribution of sheep at the national, regional and local levels. Dingo predation contributed substantially to the historical contraction of the sheep industry to its present-day distribution, which is almost exclusively confined to areas within fenced dingo exclusion zones. Dingo populations and/or their influence are now present and increasing in all sheep production zones of Australia, inclusive of areas that were once dingo free'. Conclusions Rangeland production of wool and sheep meat is predicted to disappear within 30-40 years if the present rate of contraction of the industry continues unabated. Understanding the influence of dingoes on sheep production may help refine disease response strategies and help predict the future distribution of sheep and their diseases.

The distribution and abundance of electrosensory pores in two benthic sharks: a comparison of the wobbegong shark, Orectolobus maculatus, and the angel shark, Squatina australis

Electroreception is an ancient sense found in many aquatic animals, including sharks, which may be used in the detection of prey, predators and mates. Wobbegong sharks (Orectolobidae) and angel sharks (Squatinidae) represent two distantly related families that have independently evolved a similar dorso-ventrally compressed body form to complement their benthic ambush feeding strategy. Consequently, these groups represent useful models in which to investigate the specific morphological and physiological adaptations that are driven by the adoption of a benthic lifestyle. In this study, we compared the distribution and abundance of electrosensory pores in the spotted wobbegong shark (Orectolobus maculatus) with the Australian angel shark (Squatina australis) to determine whether both species display a similar pattern of clustering of sub-dermal electroreceptors and to further understand the functional importance of electroreception in the feeding behaviour of these benthic sharks. Orectolobus maculatus has a more complex electrosensory system than S. australis, with a higher abundance of pores and an additional cluster of electroreceptors positioned in the snout (the superficial ophthalmic cluster). Interestingly, both species possess a cluster of pores (the hyoid cluster, positioned slightly posterior to the first gill slit) more commonly found in rays, but which may be present in all benthic elasmobranchs to assist in the detection of approaching predators.

Exploiting the beta distribution-based reputation model in recommender system

Reputation systems are employed to measure the quality of items on the Web. Incorporating accurate reputation scores in recommender systems is useful to provide more accurate recommendations as recommenders are agnostic to reputation. The ratings aggregation process is a vital component of a reputation system. Reputation models available do not consider statistical data in the rating aggregation process. This limitation can reduce the accuracy of generated reputation scores. In this paper, we propose a new reputation model that considers previously ignored statistical data. We compare our proposed model against state-of the-art models using top-N recommender system experiment.

Single network adaptive critic design for power system stabilisers

The recently developed single network adaptive critic (SNAC) design has been used in this study to design a power system stabiliser (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. PSS design is formulated as a discrete non-linear quadratic regulator problem. SNAC is then used to solve the resulting discrete-time optimal control problem. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a single machine infinite bus test system for various system and loading conditions. The proposed stabiliser, which is relatively easier to synthesise, consistently outperformed stabilisers based on conventional lead-lag and linear quadratic regulator designs.

Vertical Distribution of Soil Denitrifying Communities in a Wet Sclerophyll Forest under Long-Term Repeated Burning

Soil biogeochemical cycles are largely mediated by microorganisms, while fire significantly modifies biogeochemical cycles mainly via altering microbial community and substrate availability. Majority of studies on fire effects have focused on the surface soil; therefore, our understanding of the vertical distribution of microbial communities and the impacts of fire on nitrogen (N) dynamics in the soil profile is limited. Here, we examined the changes of soil denitrification capacity (DNC) and denitrifying communities with depth under different burning regimes, and their interaction with environmental gradients along the soil profile. Results showed that soil depth had a more pronounced impact than the burning treatment on the bacterial community size. The abundance of 16S rRNA and denitrification genes (narG, nirK, and nirS) declined exponentially with soil depth. Surprisingly, the nosZ-harboring denitrifiers were enriched in the deeper soil layers, which was likely to indicate that the nosZ-harboring denitrifiers could better adapt to the stress conditions (i.e., oxygen deficiency, nutrient limitation, etc.) than other denitrifiers. Soil nutrients, including dissolved organic carbon (DOC), total soluble N (TSN), ammonium (NH4 +), and nitrate (NO3 −), declined significantly with soil depth, which probably contributed to the vertical distribution of denitrifying communities. Soil DNC decreased significantly with soil depth, which was negligible in the depths below 20 cm. These findings have provided new insights into niche separation of the N-cycling functional guilds along the soil profile, under a varied fire disturbance regime.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.